Journal of Frontiers of Computer Science and Technology ›› 2016, Vol. 10 ›› Issue (10): 1365-1375.DOI: 10.3778/j.issn.1673-9418.1508004

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Group Reverse k Nearest Neighbor Query Based on Voronoi Diagram in Spatial Databases

ZHANG Liping+, LIU Lei, LI Song, YU Jiaxi   

  1. College of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China
  • Online:2016-10-01 Published:2016-09-29

空间数据库中基于Voronoi图的组反k最近邻查询

张丽平+,刘  蕾,李  松,于嘉希   

  1. 哈尔滨理工大学 计算机科学与技术学院,哈尔滨 150080

Abstract: To overcome the limitation of query objects in group reverse k nearest neighbor (GRkNN) query, this paper proposes the group reverse k nearest neighbor query method based on Voronoi diagram (V_GRkNN). The proposed method finds data points that take any point in the query objects set as one of their k nearest neighbors. In the practical application, V_GRkNN query can be used to evaluate the influence of a group of query objects. Firstly, the query points set Q is optimized in order to reduce the effect of the query points number on query efficiency, the data points set P is pruned to reduce the searching ranges. And then according to the pruning strategies based on Voronoi diagram, the candidate set is filtered. Finally, a refinement process is used to get the query's final results. The V_GRkNN method greatly improves the query speed and efficiency. Theoretical research and experiments show that the efficiency of the proposed V_GRkNN method obviously outperforms other algorithms.

Key words: Voronoi diagram, reverse k nearest neighbor, group reverse k nearest neighbor, index structure

摘要: 为了改进现有的组反k最近邻查询算法的查询速度与准确度,提出了一种基于Voronoi图的组反k最近邻查询方法(group reverse k nearest neighbor guery method based on Voronoi diagram,V_GRkNN)。该方法获得的结果集是将这组查询点中任意一点作为kNN的数据点集合,在实际应用中可以用来评估一组查询对象的影响力。该方法的特点是首先对查询点集Q进行优化处理,降低查询点数量对查询效率的负面影响;接着对数据点集P进行约减,缩小查询搜索范围;然后根据基于Voronoi图的剪枝策略对候选集进行过滤;最后经过精炼获得GRkNN查询的结果集。该方法在数据集处理阶段很大程度上提高了查询速度,在过滤、精炼阶段利用Voronoi图的特性提高了查询的准确性。理论研究和实验表明,所提方法的效率明显优于可选的已有方法。

关键词: Voronoi图, k最近邻, 组反k最近邻, 索引结构